摘要
属性约简和属性值约简是基于粗集理论进行有导师学习的基础,在分析经典约简算法的基础上,根据粗集理论中属性的依赖度和重要度等性质,提出一种改进的约简方法,以获取简洁的决策规则,从而使有导师学习变得既快捷又准确.并通过实例验证了该算法的正确性和有效性.
Attribute reduction and value reduction are the basis of learning from examples based on rough set. This paper studies the problem of attribute reduction firstly. Then, it puts forward an improved reduction algo-rithm based on the dependence and importance of attribute to get compact rules, which improves the efficiency of learning from examples. Lastly, the correctness and effectiveness of the new algorithm are shown bv an examnle.
出处
《昆明理工大学学报（理工版）》
2008年第3期122-124,共3页
Journal of Kunming University of Science and Technology(Natural Science Edition)
关键词
粗糙集
机器学习
属性约简
rough set
machine learning
attribute reduction
